UQ-bio Summer School

__imaging

Module 1: Single-Cell Optical Microscopy Experiments and Image Processing (June 7-11)

[Learning Objectives] [Schedule] [Module Materials] [Practice]

The goal of Module 1 is to get started using Python for some common single-cell image processing tasks. For this, we will again be using Google Colab to share codes and scripts.  At the end of this module, you should recognize the different labeling and microscopy approaches that scientists use to quantify single-cell behavior.  You should also be aware of, and have a little practice in, approaches to process single-cell images or videos to (1) segment (or draw outlines of) individual cells within an image and (2)  track individual molecules they move within a cell or individual cells as they move on a microscope slide.

Learning Objectives

    • Learn about different modern microscopy techniques
    • Learn about different fluorescent labeling techniques used in single-cell research
    • Learn how to apply basic image processing tools to extract single-cell data

Schedule

(Black = Open to All, Purple = Full Participants Only).

All times listed in PDT, UTC-7.

Registration is required to obtain links for live events or to join the associated Slack discussions. To register, please visit: https://forms.gle/DPMqULzTD1vG1dv68

  • 08:00 – 10:00  Tutorial 1A, Single-Cell Segmentation in Python (Dr. Zachary Fox)
  • Various Times — Mentoring Meetings
  • 08:00 – 09:00 Invited Talk, Mary Dunlop, Boston University
    • Title: Measuring and Controlling Gene Expression Dynamics in Single Bacteria
    • Abstract: Cell-to-cell heterogeneity in gene expression and growth can have critical functional consequences, such as determining whether individual bacteria survive or die following antibiotic exposure. In this talk, I will describe experiments using single-cell time-lapse microscopy to measure gene expression and growth in Escherichia coli, focusing on genes related to stress response. In support of this, I will describe our recent advances in automated image processing of time-lapse microscopy images using a deep learning model (DeLTA). Once trained, this algorithm requires minimal input from the user and can rapidly segment, track, and reconstruct lineages for bacteria growing in microfluidic chips and on two dimensional surfaces.
    • Paper: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1007673
  • 09:30 – 11:00 Career Panel Discussion, applying for and choosing the right graduate program (e.g., what to look for, who to contact, how to evaluate different options)
    • Panelists: Ilya Nemenman (Emory), Meena Balgopal (CSU), Douglas Shepherd (ASU), Linda Forero (CSU)
    • Moderator: Brian Munsky (CSU)
  • Various Times — Mentoring Meetings
  • 08:00 – 09:00 Invited Talk, Khuloud Jaqaman, UT Southwestern Medical Center
    • Title: Quantitative analysis receptor spatiotemporal organization and signaling

    • Abstract: There is mounting evidence that cell surface receptor organization plays an important role in cell signaling. We develop quantitative imaging and computational analysis approaches to study the spatiotemporal organization of cell surface receptors, with particular focus on the receptor tyrosine kinase VEGFR2 (Vascular Endothelial Growth Factor Receptor 2) and its signaling partners in endothelial cells. Using live-cell single-molecule analysis, we found that VEGFR2 exhibits both motion and oligomerization state heterogeneity in its resting state, and that its activation steps by ligand depend on its state prior to ligand binding. Using novel conditional colocalization analysis tools, we also found that the interactions of VEGFR2 with is downstream effectors exhibit spatial compartmentalization on the cell surface, possibly to enhance their signaling efficiency.

    • Publication link: https://www.sciencedirect.com/science/article/pii/S2211124720311761?via%3Dihub
  • 09:30 – 11:00 Special Workshop in Diversity Equity and Inclusion in STEM, Lisa Weber and Keisha Cook
  • Various Times — Mentoring Meetings
  • 08:00 – 10:00  Tutorial 1B, Single-Particle Tracking in Python (Dr. Luis Aguilera)
  • Various Times — Mentoring Meetings
  • 08:00 – 10:00 – Student Project/Problem Presentations and Discussions
  • 10:00 and onward – Python Hacking and Help Sessions
  • Various Times — Mentoring Meetings

Suggested Reading and Preliminary Materials

It is recommended that you go through the materials below over the weekend before attending the live zoom tutorial on June 7.

In this section, we will discuss the most common and up-to-date methods to label proteins and nucleic acids for the visualization of transcription and translation in fixed and live cells. We recommend you reading and watching the following materials: General description of Labeling Proteins for Single-Molecule Imaging by photometrics. Review on tools to image gene expression in single cells by Pichon et al., 2018. Review on NCT to image translation in live cells by Cialek et al., 2020. Linda’s Lecture Slides-Part1. Linda’s Lecture Slides-Part2.

In this video, Prof Douglas Shepherd introduces different techniques for fluorescence microscopy.

 

In this second part, Dr. Shepherd discusses the use of fluorescence microscopy for single-cell imaging.

Please see the Tutorial 0A on June 1  and the first Python Hacking and Help session from June 3.  These are both posted at Mod-0 Python.

Practice and Tutorials

On June 7, from 08:00-10:00, we will hold a preliminary tutorial on using Python for single-cell image segmentation.  The tutorial materials are available at:

On June 10, from 08:00-10:00, we will hold a preliminary tutorial on using Python for single-particle tracking. The tutorial materials are available at:

The recorded video of the tutorials will be posted below.

Recordings of Live Lectures

Recorded lectures and tutorials will be posted below.

This is the recording of Dr. Zach Fox’s tutorial on image segmentation in Python.  To follow along with the tutorial, you will need to open the Colab tutorial at: [Zach’s Segmentation Colab Tutorial]

Professor Dunlop’s invited lecture has been recorded, but is only available to individuals upon request.  If you would like access to the recording of her lecture, please contact the UQBIO organizers at qbio_summer_school@colostate.edu.

Career Panel Discussion 1: Applying for and choosing the right graduate program (e.g., what to look for, who to contact, how to evaluate different options) Panelists: Prof. Meena Balgopal (Colorado State University), Prof. Ilya Nemenman (Emory University), Prof. Douglas Shepherd (Arizona State University), Dr. Linda Forero Quintero (Colorado State University)

 Invited Talk, Khuloud Jaqaman, UT Southwestern Medical Center

  • Title: Quantitative analysis receptor spatiotemporal organization and signaling

  • Abstract: There is mounting evidence that cell surface receptor organization plays an important role in cell signaling. We develop quantitative imaging and computational analysis approaches to study the spatiotemporal organization of cell surface receptors, with particular focus on the receptor tyrosine kinase VEGFR2 (Vascular Endothelial Growth Factor Receptor 2) and its signaling partners in endothelial cells. Using live-cell single-molecule analysis, we found that VEGFR2 exhibits both motion and oligomerization state heterogeneity in its resting state, and that its activation steps by ligand depend on its state prior to ligand binding. Using novel conditional colocalization analysis tools, we also found that the interactions of VEGFR2 with is downstream effectors exhibit spatial compartmentalization on the cell surface, possibly to enhance their signaling efficiency.

  • Publication link: https://www.sciencedirect.com/science/article/pii/S2211124720311761?via%3Dihub

In this tutorial, you will learn how to track single particles using some basic Python tools and using TrackPy. Here are the links to Luis’s Colab Notebooks so you can follow along with the lesson:

Part 1: https://colab.research.google.com/drive/1qYeZLnYlk7l4W2-6oQj96CMrQQjqAcpg?usp=sharing

Part 2: https://colab.research.google.com/drive/1FcudIyndrXDOmYadUXlPgDOIP6yNP0ZZ?usp=sharing